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All Journal Dinamik Jurnal Simetris Telematika Jurnal Transformatika Jurnal Informatika Upgris Jurnal Sains dan Informatika Jurnal Pengembangan Rekayasa dan Teknologi JSiI (Jurnal Sistem Informasi) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Sistem Informasi dan Informatika (SIMIKA) Abdimasku : Jurnal Pengabdian Masyarakat Indonesian Journal of Data and Science Aiti: Jurnal Teknologi Informasi JUSTIN (Jurnal Sistem dan Teknologi Informasi) Malcom: Indonesian Journal of Machine Learning and Computer Science Tematik Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) The Indonesian Journal of Computer Science Advance Sustainable Science, Engineering and Technology (ASSET) Systematic Literature Review Journal Jurnal DIMASTIK Indonesian Journal of Infomatics
Nurtriana Hidayati
Universitas Semarang
Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Nursing Public Health Social Sciences Transportation Other

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OPTIMALISASI APLIKASI BILLING INTERNET DALAM PEMBELIAN KUOTA PADA BUMDES BERKAH AMANAH DESA TRUKO KENDAL Hidayati, Nurtriana; Wakhidah, Nur; Nugroho, Atmoko
Jurnal DIMASTIK Vol. 1 No. 2 (2023): Juli
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/dimastik.v1i2.7286

Abstract

BUMDes merupakan usaha desa yang dibentuk/didirikan oleh pemerintah desa dimana kepemilikan modal dan pengelolaannya dilaksanakan oleh pemerintah desa dan masyarakat (Putu, 2020). Mitra dari kegiatan PkM ini adalah Desa Truko Kecamatan Kangkung Kendal yang sudah memiliki badan usaha mandiri yang dijalankan melalui BUMDes yang bernama “Berkah Amanah”. Usaha yang sudah berjalan salah satunya berupa pelayanan kuota internet yang telah diprakarsai oleh desa dan dikelola oleh BUMDes yang dalam hal ini diberi nama “Billing Internet”. Adapun kendalanya adalah saat ini belum terdapat digitalisasi dalam pengelolaannya. Untuk memenuhi kebutuhan pengelolaan pembayaran internet maka dibangun aplikasi otomatisasi yang mampu berjalan secara online atau offline sehingga akan menjadikan lebih cepat dalam melayaninya. Melalui kegiatan Pengabdian Kepada Masyarakat ini aplikasi yang dihasilkan disosialisasikan kepada pengelola BUMDes “Berkah Amanah” sebanyak 20 peserta dengan menunjukkan adanya peningkatan pemahaman ketertarikan dan cara penggunaan aplikasi Billing Internet tersebut sebesar 85,5%.
PENINGKATAN KEMAMPUAN MEMBANGUN ANIMASI TIGA DIMENSI (3D) MENGGUNAKAN APLIKASI BLENDER PADA SISWA SMK NU 01 KENDAL Hidayati, Nurtriana; Zaman, Badroe; Handayani, Titis
Jurnal DIMASTIK Vol. 3 No. 1 (2025): Januari
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/dimastik.v3i1.11670

Abstract

SMK Nahdlatul ‘Ulama (NU) 01 Kendal adalah Sekolah Kejuruan kelompok Bisnis – Manajemen dan Pariwisata dibawah naungan Lembaga Pendidikan Ma’arif NU Kabupaten Kendal. SMK NU 01 Kendal memiliki 7 (tujuh) kompetensi keahlian salah satunya yakni Rekayasa Perangkat Lunak. Jurusan Rekayasa perangkat lunak atau biasa disebut RPL menawarkan beberapa keahlian dibidang teknologi informasi berupa pemrograman, selain itu juga diajarkan mengenai desain dengan menggunakan Photoshop, Corel Draw, dan lainnya. Desain animasi tiga dimensi (3D) belum menjadi muatan yang diajarkan oleh SMK NU 01 Kendal dalam jurusan RPL. Di era ini, desain animasi 3D menjadi fokus bidang yang menarik dalam industri multimedia. Maka pada PkM ini akan memberikan pelatihan membuat animasi 3D menggunakan aplikasi Blender. Aplikasi Blender merupakan salah satu program animasi 3D yang sifatnya open source. Aplikasi Blender digunakan untuk membuat model 3D, animasi, efek visual, model cetak 3D, dan permainan video. Hasil dari kegiatan yang di ikuti oleh 12 siswa RPL ini menunjukan bahwa ada peningkatan kemampuan mengetahui aplikasi blender dan memahami membangun desain 3D dari sebelum kegiatan hanya 9,7% yang merespon denga jawaban Ya, namun setelah pelatihan dalam hasil post-test menunjukkan adanya peningkatan dari 12 responden yang menjawab Ya menjadi sebesar 92,7%. Hal ini memberikan arti bahwa pengabdian yang kami lakukan berhasil.
A Systematic Review on Data Fusion Techniques for Agri-cultural Yield Prediction: Integrating Satellite Imagery with Climatic Data Khoirudin, Khoirudin; Pungkasanti, Prind Triajeng; Hidayati, Nurtriana
Systematic Literature Review Journal Vol. 1 No. 4 (2025): October: Systematic Literature Review Journal
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/slrj.v1i4.245

Abstract

An answer to the worldwide need for solutions to food security, data fusion technology that combines climate data with satellite imagery greatly improves the accuracy of agricultural yield predictions; this study intends to examine the advancements, methods, and key contributions of this area. By sifting through 62 papers pulled from Scopus, this research employs the SLR methodology. Document type, data source, open access, subject area, and year of publication (2020–2024) are some of the categories filtered through by Boolean keywords in the selection process. To assess patterns in publications, the efficacy of machine learning models, and key contributions, bibliometric analysis was performed. An upward tendency in publication has been identified by the analysis, particularly beyond the year 2023. Integrating geographical and temporal data has been a great success with machine learning models like Random Forest, Random Forest, and Gradient Boosting. Data resolution, integration of data from several sources, and a real-time framework are still missing pieces to the puzzle when it comes to generalizing research outcomes. More complex data fusion approaches, multiregional datasets, and advanced machine learning models to back more accurate agricultural predictions are all things that this study notes as needing additional investigation in the future. To further innovate agricultural yield prediction, multidisciplinary collaboration is also crucial.
Peningkatan Kemampuan Teknologi ChatGPTUntuk Administrasi Para Guru SMA Masehi 2 PSAK Hirzan, Alauddin Maulana; Daru, April Firman; Hidayati, Nurtriana; Hartanto, Agus
Jurnal DIMASTIK Vol. 4 No. 1 (2026): Januari
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/dimastik.v4i1.12716

Abstract

Tenaga pendidik dan staf administrasi di SMA Masehi 2 PSAK menghadapi tantangan dalam mengelola tugas administratif secara efisien akibat keterbatasan pemanfaatan teknologi berbasis kecerdasan buatan. Oleh karena itu, kegiatan pengabdian ini bertujuan untuk meningkatkan keterampilan mereka dalam menggunakan ChatGPT sebagai alat bantu dalam penyusunan dokumen administratif, surat-menyurat, dan laporan akademik. Metode yang digunakan adalah pelatihan langsung (hands-on training) yang mencakup sesi ceramah dan praktik langsung. Evaluasi kegiatan dilakukan melalui kuesioner pre-test dan post-test untuk mengukur peningkatan pemahaman peserta. Hasil evaluasi menunjukkan adanya peningkatan pemahaman peserta secara signifikan, dimana skor pemahaman keseluruhan meningkat dari 63% menjadi 82%. Diharapkan, kegiatan ini dapat meningkatkan efisiensi kerja, mengurangi beban administratif, serta mendukung transformasi digital di SMA Masehi 2 PSAK.
Evaluasi Kinerja Model Long Short-Term Memory dan Gated Recurrent Unit untuk Prediksi Magnitude Gempa Bumi Di Indonesia Nugraha, Giananda Saktika; Priyambodo, Pamungkas Haryo; Rahmayuna, Novita; Hidayati, Nurtriana
Dinamik Vol 31 No 1 (2026)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v31i1.10375

Abstract

This study aims to evaluate and compare the performance of two neural network architectures under the Recurrent Neural Network (RNN) category, namely Gated Recurrent Unit (GRU) and Long Short-Term Memory (LSTM), in predicting earthquake magnitude in Indonesia. The dataset used consists of daily earthquake magnitude records from 2008 to 2023, preprocessed into time series format and normalized using the MinMax method. The training process was conducted using various combinations of batch size and epoch, and evaluated using Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and relative prediction accuracy. The evaluation results show that LSTM with a batch size of 32 and 50 epochs provides the best prediction performance, achieving a MAE of 0.2227 and 93.65% accuracy. Meanwhile, GRU performed optimally at a batch size of 64 and 50 epochs, with a MAE of 0.2229 and 93.66% accuracy. The prediction visualization shows that LSTM offers greater stability and precision in tracking actual data patterns. These findings indicate that LSTM holds stronger potential for supporting earthquake prediction systems based on time series data.
ESTIMASI LAJU PERTUMBUHAN PENDUDUK DI KABUPATEN JEPARA DENGAN PENDEKATAN REGRESI LINIER BERGANDA Hetta Rachma; Mutiatun Nafisah; Nurtriana Hidayati
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 8 No. 1 (2025): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/simika.v8i1.3790

Abstract

One of the main factors in planning the development of a region is the change in population. A rapid population growth rate can have adverse effects, such as poverty, unemployment, and a decrease in the quality of human resources. The purpose of this study is to predict the population growth rate in Jepara Regency by applying the multiple linear regression method, which can be used as a basis for the government in planning strategies to improve the economy, infrastructure, and other sectors, so that in the end it can have an impact on improving the welfare and quality of life of the community. The data used was obtained from BPS Jepara Regency for the period 2019-2023. Multiple linear regression analysis was applied as the method, with the number of males (X1) and females (X2) as independent variables, and the total population (Y) as the dependent variable. Based on the analysis, the predicted population in 2024 is 1,264,598 people, the same number as in 2023, indicating a stagnant growth condition. The results of this study provide important implications for government policy planning, especially in infrastructure development strategies, economic improvement, and human resource processing. The multiple linear regression method is effective in providing an accurate estimation picture, and can be the basis for future decision-making.
Analisis dan Pengembangan Sistem Informasi Kemahasiswaan Berbasis E-Letter dengan Menggunakan User Centered Design Karunia, Reiza Dwi; Hidayati, Nurtriana
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.3755

Abstract

SISKA adalah sebuah sistem informasi yang memuat mengenai informasi dan kegitan Kemahasiswaan Universitas Semarang. SISKA Sudah berjalan 2 tahun, berdasarkan pengguna SISKA masih memiliki kekurangan danbelum sesuai kebutuhan. Untuk mengetahui ketepatan tersebut sesuai atau tidak, maka disebarlah kuisioner terhadap 26 Responden yang mana terdiri dari Admin dan Mahasiswa yang memiliki hak akses SISKA pada Organisasi Mahasiswa. Dalam organisasi mahsiswa SISKA sebagai tempat mengupload surat menyurat, proposal kegiatan maupun Laporan Pertanggung jawaban kegiatan. Proposal ini dibuat untuk menganalisis serta mengembangkan SISKA agar sesuai dengan Kebutuhan. Pada proses pengembangan sistem ini menggunakan metode User Centered Design (UCD) serta untuk Analisis sistemnya menggunakan perhitungan Kuisioner SUS.
Integrating Multimodal Data Processing Techniques to Enhance User Experience Evaluation in Interactive Digital Platforms Khoirudin Khoirudin; Nurtriana Hidayati
Indonesian Journal of Infomatics Vol. 1 No. 1 (2026): February: Indonesian Journal of Infomatics
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/iji.v1i1.26

Abstract

User experience (UX) evaluation plays a crucial role in understanding how users interact with digital platforms and in improving product design. Traditional UX evaluation methods, such as surveys and interaction logs, often rely on a single data source, which limits the depth of analysis. This study explores the integration of multimodal data processing techniques in UX research, aiming to enhance the accuracy and comprehensiveness of UX evaluations. By combining interaction logs, visual attention data, and physiological measurements, this approach provides a more holistic understanding of user behavior, emotional responses, and satisfaction. Interaction logs offer objective data on user actions, while eye-tracking and physiological data capture users' emotional states, providing richer insights into usability and user experience. This study highlights the effectiveness of multimodal integration in identifying patterns that traditional methods overlook, such as emotional responses to interface elements and real-time feedback from users. The findings reveal that multimodal data processing improves the precision of UX assessment by combining objective behaviors with subjective emotional responses, offering a more complete view of user interactions. The study also discusses the challenges of data synchronization and the potential ethical concerns related to the use of physiological data. The integration of these data sources shows great potential for enhancing the design process, allowing designers to make informed decisions based on comprehensive insights. Finally, this research underscores the future potential of multimodal analytics in UX research, suggesting further exploration of additional data modalities and real-time applications in various digital environments.
Co-Authors Agus Hartanto Agusta Praba Ristadi Pinem Alauddin Maulana Hirzan April Firman Daru Ardima, Muhammad Basyier Aryash, Muhana Fadhillah Astuti, Rizka Yuli Atmoko Nugroho Aziza, Luthfiah Nur Cholil, Saifur Rohman Devila, Laras Elza Edi Widodo, Edi Eka Putri Rachmawati Faturahman, Rinaldo Dwi Hassanudin, Wahyu Maulana Henny Indriyawati Hetta Rachma Irfan, Muhammad Nur Joko Suntoro Karunia, Reiza Dwi Khoirudin Khoirudin Khoirudin Khoirudin, Khoirudin Kholidin Kholidin Lenny Margaretta Huizen Maulana, Bagas Akbar Maulana, Daffa Muhammad Basyier Ardima Mutiatun Nafisah Nugraha, Giananda Saktika Nur Wakhidah Pratama, Ericx Cahaya Prind Triajeng Pungkasanti, Prind Triajeng Priyambodo, Pamungkas Haryo Rachma, Hetta Rahmayuna, Novita Sekar Cinta Amaria Setiaji, Galet Guntoro Susanto Susanto Suwari, Dewi Ratna Titin Winarti Titis Handayani Vensy Vydia Victor Gayuh Utomo Weulartafella, Mifthahul Pratama Widhianti, Sekar Elok ZAMAN, BADROE